ATLAS Offline Software
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This package does data monitoring providing algorithms and tools which can give bytestream errors, efficiencies, noises, occupancies, Lorentz angles, tracking quantities for the SCT detector for both online and offline. The histograms are published and used in the Online Histogram Presenter (OHP).
In the new data quality motitoring framework for Run 3, algorithms inherited directly from AthMonitorAlgorithm are used.
In the old data quality monitoring framework up to Run 2, tools inherited directly from ManagedMonitorToolBase are used. Tools will be removed at some point.
Here are the active monitoring algorithms / tools:
InnerDetector/InDetMonitoring/SCT_Monitoring/python/SCTMonitoringConfig.py is the main configuration script.
When the Reco_tf.py command is used, the chain is the following:
InnerDetector/InDetExample/InDetRecExample/share/InDetMonitoringSCT.py is the main configuration script. To use the new DQ framework, the useNewAlgs flag in the script has to be set True. The default value is True.
When the Reco_tf.py command is used, the chain is the same as above up to DataQualitySteering_jobOptions.py. The following chain is:
InnerDetector/InDetExample/InDetRecExample/share/InDetMonitoringSCT.py is the main configuration script too. To use the new DQ framework, the useNewAlgs flag in the script has to be set False. The default value is True. The chain is the same as above.